前向碰撞预警系统：用现场数据验证驾驶模拟器结果
Forward Collision Warning Systems: Validating Driving Simulator Results with Field Data
摘要：
随着先进驾驶辅助系统（ADAS）的出现，在使用这种技术时越来越需要评估驾驶员行为。在这项独特的研究中，在驾驶模拟器环境中引入了一个使用互联车辆技术的前向碰撞警告（FCW）系统，以评估驾驶员的制动行为，然后使用现场测试数据对结果进行验证。本研究共招募了93名参与者，并创建了南巴尔的摩的虚拟网络。进行单样本t检验，发现FCW后速度平均降低15.07 mph，具有统计学显著性。随机森林、机器学习算法被认为是按重要性顺序对数据集中最重要的变量进行排序的最佳方法。从密歇根大学交通研究所（UMTRI）获得的现场数据，证实了FCW的调查结果，从这个驾驶模拟器的研究。
英文摘要：
With the advent of Advanced Driver Assistance Systems (ADAS), there is an increasing need to evaluate driver behavior while using such technology. In this unique study, a forward collision warning (FCW) system using connected vehicle technology, was introduced in a driving simulator environment, to evaluate driver braking behavior and then the results are validated using data from field tests. A total of 93 participants were recruited for this study, for which a virtual network of South Baltimore was created. A one sample t-test was conducted, and it was found that the mean reduction in speed of 15.07 mph post FCW, is statistically significant. A random forest, machine learning algorithm was found to be the best fit for ranking the most important variables in the dataset by order of importance. Field data obtained from the University of Michigan Transportation Research Institute (UMTRI), substantiated the FCW findings from this driving simulator study.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
